This invention relates to communication systems and, more particularly, to characterization of the signal characteristics of a communication channel.
Public cellular networks (public land mobile networks) are commonly employed to provide voice and data communications to a plurality of subscribers. For example, analog cellular radiotelephone systems, such as designated AMPS, ETACS, NMT-450, and NMT-900, have been deployed successfully throughout the world. More recently, digital cellular radiotelephone systems such as that designated as IS-54B (and its successor IS-136) in North America and the pan-European GSM system have been introduced. These systems, and others, are described, for example, in the book titled Cellular Radio Systems by Balston, et al., published by Artech House, Norwood, Mass., 1993. In addition, satellite based radio communication systems are also being utilized to provide wireless communications in various regions such as the Asian Cellular Satellite System (ACeS) generated by Lockheed Martin Corporation.
Wireless communications systems such as cellular radiotelephone systems typically include a plurality of communication channels which may be established between a first transceiver (such as a base station) and a second transceiver (such as a mobile terminal). The communication channels typically are subject to performance-degrading environmental effects such as multi-path fading and interference or other noise source effects. Interference effects may be caused by interaction of non-orthogonal signals generated in the signal medium by sources other than the source of the desired transmitted signal.
One significant source of interference signals results, in part, from the limited range of radio channels allocated to cellular mobile communications in the United States. The limitations on the number of available frequency bands present several challenges as the number of subscribers increases. Increasing the number of subscribers in a cellular radiotelephone system generally requires more efficient utilization of the limited available frequency spectrum in order to provide more total channels while maintaining communications quality. This challenge is heightened because subscribers may not be uniformly distributed among cells in the system. More channels may be needed for particular cells to handle potentially higher local subscriber densities at any given time.
For these reasons, conventional cellular systems typically employ frequency reuse to increase potential channel capacity in each cell and increase spectral efficiency. Fixed frequency reuse generally involves allocating frequency bands to each cell, with cells employing the same frequencies geographically separated to allow radiotelephones in different cells to simultaneously use the same frequency without interfering with each other. An alternative approach to fixed frequency reuse is adaptive channel allocation (ACA). In ACA networks, the available channels are typically dynamically allocated throughout the network to maximize system capacity rather than defining a specific subset of the available channels for each cell within the network.
The allocation of a channel within cellular networks to a mobile terminal may be based on measurements made by the mobile terminal and/or the network of channels (or frequencies) which are potential sources of interference signals as well as signal strengths of desired signals to calculate the carrier (or signal) to interference ratios. The interference signal measurements and signal to interference ratio values may, in turn, be used to select a channel for use by the mobile terminal which may provide, for example, acceptable performance at the lowest transmission power level. Studies have shown power control based on carrier to interference ratio provides better results than when based on signal strength as discussed in J. Zander, xe2x80x9cPerformance of Optimum Transmitter Power Control in Cellular Radio Systems,xe2x80x9d IEEE Trans. Veh. Tech., February 1992, pp. 57-62.
In a multi-rate system, rate adaptation can be performed, for example, based on carrier to interference ratio measurements. Knowledge of the carrier to interference ratio can also be used to tune algorithms (such as a channel tracker) that can use knowledge of the impairment variance on a channel. Thus, it is desirable to perform carrier to interference measurements in devices such as mobile terminals in a cellular telephone system. Recognizing the benefits of making such measurements, for example, the IS-136 Rev. B. standard includes measurement and reporting procedures for carrier to interference ratio measurements.
Various methods have been proposed to measure interference power which measurements may then be used in generating a carrier to interference ratio for a channel. One such proposed method is the interference projection method. This method essentially works by projecting the received signal onto the null space of a known symbol pattern such as a synchronization pattern. The residual energy present provides the interference power whereas the signal or carrier power can be obtained by averaging the power of the received signal. An example of such an approach is discussed in M. D. Austin and G. L. Stuber, xe2x80x9cIn-Service Signal Quality Estimation for TDMA Cellular Systems,xe2x80x9d PIMRC""95, pp. 836-840. The interference projection method is generally considered to provide a poorer performance than various of the other proposed methods.
Another proposed method for measurement is the subspace based method. Under this method, the dimensions of the signal and interference subspaces are typically identified using an eigen-value decomposition of the correlation matrix of the received signal and the corresponding powers give the signal and interference powers. While this method generally gives good performance, it may involve quite complex calculations. An example of a subspace based method is discussed in M. Andersin, N. B. Mandayam and R. D. Yates, xe2x80x9cSubspace Based Estimation of the Signal to Interference Ratio for TDMA Cellular Systems,xe2x80x9d IEEE VTC""96, pp. 1155-1159.
A third approach involves demodulation based methods. In demodulation based methods, the received data is demodulated and the error between a hypothesized signal and the received signal is used to estimate the interference power. This method typically does not work well at low signal to interference ratios due to demodulation errors. While improved performance in demodulation methods can be provided by using decoded and re-encoded data, the problems at low signal to interference ratios still generally remain. An example of a demodulation based method is described in K. Balachandran, S. Kadaba and S. Nanda, xe2x80x9cRate Adaptation Over Mobile Radio Channels Using Channel Quality Information,xe2x80x9d IEEE Globe-com""98 Communications Theory Mini Conference Record, pp. 46-52.
A further method previously proposed is the signal projection method. Using this method, a best fit channel is typically obtained using the received signal and knowledge of a known or an expected received symbol pattern such as a synchronization sequence. The error in the best fit approximation is appropriately scaled to provide an estimate of the interference power on a per symbol basis. This method generally works as well as the subspace based method at a lower complexity. However, problems may be encountered with the conventional signal projection method on channels subject to high doppler frequencies where the best fit channel varies over the duration of the synchronization word being used for the signal projection analysis. This time variation, in turn, may lead to errors in the interference power measurement using the signal projection method. The primary cause of this error condition in systems such as mobile cellular networks is multi-path fading resulting from movement of the mobile terminal during measurements.
It is, therefore, an object of the present invention to provide systems and methods which may allow improved estimation of the carrier to interference ratio of a communication channel.
In order to provide for the foregoing and other objectives, a method is provided which calculates a carrier to interference ratio of a channel using an approach which accounts for variations in the channel response characteristics over the estimation evaluation time period. The time variations may be taken into account by various alternative approaches including breaking the sample period into a series of sub-sample estimation windows and applying a different constant channel response estimate to each sub-sample estimation window or by applying a time varying model to the channel when generating the channel response estimate (such as a least squares error fit to a first order or higher order equation). Accordingly, the systems and methods of the present invention may provide for improved estimates of the carrier to interference ratio, particularly for channels subject to multi-path fading effects such as those which may result from movement of a mobile terminal during measurements of the channel.
In one embodiment of the present invention, a method is provided for estimation of interference on a communication channel. A signal is received over the channel over a period of time and the received signal is demodulated to provide an associated plurality of symbol estimates for the period of time. The plurality of symbol estimates is compared to a plurality of associated expected symbols to generate a channel estimate which accounts for variation of the channel over the period of time and an estimate of interference signal strength for the channel is generated using the channel estimate and the signal received over the period of time. The period of time may be within a single received slot. A carrier to interference ration for the channel may be determined using the interference signal strength.
In another embodiment, the comparing step includes the steps of defining a time varying function for the channel estimate, the time varying function including a plurality of coefficients, and estimating each of the plurality of coefficients based on the plurality of symbol estimates and the plurality of associated expected symbols. Furthermore, the steps of receiving, demodulating, comparing and generating may be repeated for a plurality of received slots. The generated interference signal strengths may be accumulated and an average interference signal strength for the channel may be generated from the accumulated interference signal strengths. More particularly, the time varying function may be a linear time varying function of the form c=c0+c1t for the channel estimate where c is the channel estimate and c0 and c1 are coefficients of the channel estimate.
In a further embodiment of the present invention, the power of the interference signal may be calculated to provide the interference signal strength using a function of the form       P    ⁢          (              I        i            )        =            1      z        ⁢          ∑                        "LeftBracketingBar"                                    r              i                        -                                          c                i                0                            ⁢                              s                i                                      -                                          c                i                1                            ⁢                              is                i                                              "RightBracketingBar"                2            
where the summation is over the time period and where Ii is the interference signal, ri is a received signal, si is an excepted signal, i is a symbol period and z is a scaling factor. In a further aspect, the period of time may be the synchronization period of the received slot and the plurality of associated expected symbols are a predetermined synchronization sequence. Alternatively, plurality of associated expected symbols may be generated from decoded and then re-coded symbol estimates corresponding to symbol estimates for the period of time.
The calculating step may include scaling the interference signal strength to a per symbol basis and the summation may be performed over the period of time on a symbol rate basis. Furthermore, the channel may be an IS-136 protocol channel in which case the synchronization period is fourteen symbols and the summation in the interference signal strength function is for i=0 to 13. In one embodiment where the channel is subject to time dispersion, the channel estimate could include multiple channel estimates, corresponding to different delayed versions of the signal, each such channel estimate varying with time. For example, the channel estimates could include a first channel estimate associated with the symbol position of the channel estimate and a second channel estimate associated with a symbol position preceding the symbol position of the channel estimate.
In another embodiment of the present invention, the period of time is partitioned into a plurality of estimation windows. A constant channel estimate ci is generated for each of the plurality of estimation windows. Each of the constant channel estimates is associated with a symbol position in a middle region of the respective estimation window associated with the constant channel estimate. Preferably, each of the plurality of estimation windows overlaps at least one other of the plurality of estimation windows. In one aspect of this embodiment, the channel may be an IS-136 protocol channel and the period of time may be the synchronization period which is fourteen symbols and the summation in the interference signal strength function may be for i=2 to 11 with a sub-synch sequence length of 5. Each of the plurality of estimation windows may be an odd symbol length estimation window having a center symbol position and the each of the constant channel estimates may be associated with the central symbol position in the estimation window associated with the constant channel estimate.
While the invention has been described above primarily with reference to methods, it is to be understood that systems are also provided.